Embodiments of the present invention relate generally to methods and systems for analyzing a collection of data and more particularly to generating natural language insights about a set of data.
There is explosion in the volume of data generated and maintained today. It is estimated that ninety percent of the data available now was generated in the last two years. Business organizations have a tough time getting value out of all the generated and collected data. Data interpretation is largely done manually using available business intelligence tools. However, these tools stop at displaying data in the form of tables and graphs. Interpretation of these tables and graphs is then left to business analysts. As a result, the insight gained from this data can be person-dependent and tool-dependent. Additionally, the typical business analyst does not have the skills in statistics, data mining, data wrangling, and programming required to effectively analyze large volumes of data. Industry has tried to solve the problem hiring data scientists who are scarce. Hence, there is a need for improved methods and systems for analyzing a set of data.